DataikuNLP

This model is a copy of this model repository from sentence-transformers at the specific commit `c4dfcde8a3e3e17e85cd4f0ec1925a266187f48e`. This is a sentence-transformers model: It maps sentences & paragraphs to a 384 dimensional dense vector space and can be used for tasks like clustering or semantic search. Using this model becomes easy when you have sentence-transformers installed: Usage (HuggingFace Transformers) Without sentence-transformers, you can use the model like this: First, you pass your input through the transformer model, then you have to apply the right pooling-operation on-top of the contextualized word embeddings. For an automated evaluation of this model, see the Sentence Embeddings Benchmark: https://seb.sbert.net If you find this model helpful, feel free to cite our publication Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks:

This model is a copy of this model repository from sentence-transformers at the specific commit `5d2b7d1c127036ae98b9d487eca4d48744edc709`. This is a sentence-transformers model: It maps sentences & paragraphs to a 300 dimensional dense vector space and can be used for tasks like clustering or semantic search. Using this model becomes easy when you have sentence-transformers installed: For an automated evaluation of this model, see the Sentence Embeddings Benchmark: https://seb.sbert.net If you find this model helpful, feel free to cite our publication Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks: